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Artificial Intelligence in Agriculture (Hardback, Rajesh Singh & Anita Gehlot, Mahesh Kumar Prajapat & Bhupendra Singh)

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Nipa Genx Electronic Resources & Solutions
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Nipa Genx Electronic Resources & Solutions

We at NIPA when look back at the journey that started 47 years ago, we feel humbled. Sh Shree Pal Jain, the Founder, started the firm with just one room, one table and a set of chairs; with his sheer dedication, hard work, commitment and to develop everlasting relationships, throughout these nearly five decades have developed a customer centric and value-based company.

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Product details

"This book is a comprehensive resource for individuals who wish to explore the potential of Artificial Intelligence (AI) in agriculture, either for the purpose of gaining a foundational understanding or expanding their existing knowledge. The book provides readers with a practical, hands-on approach to learning about AI, machine learning, deep learning, computer vision, and expert systems, with real-world examples to aid comprehension.

Furthermore, the book includes an introduction to the basics of Python programming, making it accessible to readers with little or no prior programming experience. The book is divided into two parts: the first part covers the fundamentals of AI in agriculture, including its various branches and their applications. The second part focuses on the implementation of algorithms and the use of different machine learning, deep learning, and computer vision libraries to develop practical and insightful projects.

Upon completion of this book, readers will have gained an understanding of the various branches of AI and their applicable scenarios, as well as the standard workflow for approaching and solving machine-learning problems. Additionally, readers will be equipped with the skills necessary to tackle real-world problems in the agriculture sector, such as crop health prediction, field surveillance analytics, and the recognition of plant species. With this knowledge, readers will be well-prepared to leverage the power of AI in the agriculture field.

"


Content


"1. Artificial Intelligence 2. Learning Python for Artificial Intelligence 3. Machine Learning 4. Deep Learning 5. Computer Vision 6. Knowledge Based Expert System 7. Tools for Artificial Intelligence 8. Important Libraries for AI 9. Machine Learning Algorithms 10. Disease Classification and Detection in Plants 11. Species Recognition in Flowers 12. Precision Farming

"


Description provided by Nipa Genx Electronic Resources & Solutions.

Offers foundational to advanced understanding of AI in agriculture.

Includes practical examples and projects.

Accessible for readers with no prior programming experience.

First part covers fundamentals; second part focuses on implementation.

Covers crop health prediction, field surveillance, and species recognition.

Authored by experts in agriculture and AI.

Guides readers on using various AI libraries effectively.

Specifications
Title
Artificial Intelligence in Agriculture
Authors
Rajesh Singh, Anita Gehlot, Mahesh Kumar Prajapat, Bhupendra Singh
Format
Hardback
Topics Covered
Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Python Programming
Target Audience
Farmers, agricultural specialists, researchers, and students
Publication Year
2023
Publisher
Not Specified
Use cases
Category
agriculture > agriculture and farm consultants > hi-tech agriculture consultants
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Wholesale, distribution and international sourcing
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Frequently asked by buyers
What is the primary focus of 'Artificial Intelligence in Agriculture'?

The book focuses on the transformative applications of AI in the agricultural sector, providing foundational knowledge as well as practical project implementation.

Can beginners understand this book?

Yes, the book includes an introduction to Python programming and is designed to be accessible for readers with little or no prior programming experience.

What are some applications covered in the book?

The book covers applications such as crop health prediction, field surveillance analytics, and plant species recognition.

Is there a structured approach to learning in this book?

Yes, the book is divided into two clear parts, with the first part focusing on fundamentals and the second on practical implementation.

Who would benefit from reading this book?

Farmers, agricultural technologists, researchers, and students interested in the intersection of technology and agriculture will all benefit from this resource.

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